The overall goal of these studies is to continue to develop and validate two complementary computational methods for discovery of novel opioid receptor ligands that could be useful analgesics with diminished respiratory depression and addiction liability. Discovery of such behaviorally selective ligands should enhance the usefulness of opioids as clinical analgesics. The working hypothesis employed is that ligands that bind with significant affinity to the three cloned opioid receptors (mu, delta, and kappa), but with different combinations of activation and inhibition properties at the three receptors, could be the most promising behaviorally selective agents. To identify such candidates, a novel method, DistComp, developed in our laboratory, will be used to obtain 3D pharmacophores that contain the common molecular determinants for ligand recognition of all three receptors and unique determinants for ligand activation of each of them. These pharmacophores will then be used to search 3D databases for compounds that fulfill their requirements. This search will lead directly to the discovery of novel candidate ligands for the opioid receptors as well as provide a validation of the 3D pharmacophores. The second computational method to be employed is structure based assessment of the novel compounds discovered as ligands for the three opioid receptors. These models will be used for simulations of explicit receptor complexes with these putative ligands. Compounds that pass both types of computational assessments will be selected for experimental determination of receptor affinities in transfected cell systems to further identify promising new ligands for the opioid receptor. PROPOSED COMMERCIAL APPLICATION Opioids remain very useful clinical analgesics with unique antinociceptive profiles. However concern about addiction liability and respiratory depression is a long standing impediment to their optimum utilization. The promising new opioid ligands identified in this study could have better separation between these end points and hence be worthwhile targets for commercial application.